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Artículo

A Complexity Measure

Thomas J. McCabe · IEEE Transactions on Software Engineering · 1976

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Author / responsible party
Thomas J. McCabe
Publisher
IEEE Transactions on Software Engineering
Year
1976
Language
English

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This paper describes a graph-theoretic complexity measure and illustrates how it can be used to manage and control program complexity. The paper first explains how the graph-theory concepts apply and gives an intuitive explanation of the graph concepts in programming terms. The control graphs of several actual Fortran programs are then presented to illustrate the correlation between intuitive complexity and the graph-theoretic complexity. Several properties of the graph-theoretic complexity are then proved which show, for example, that complexity is independent of physical size (adding or subtracting functional statements leaves complexity unchanged) and complexity depends only on the decision structure of a program.

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APA 7

McCabe, T. J. (1976). A Complexity Measure. https://doi.org/10.1109/tse.1976.233837

MLA

McCabe, Thomas J. "A Complexity Measure." 1976. https://doi.org/10.1109/tse.1976.233837.

Chicago

McCabe, Thomas J. 1976. "A Complexity Measure.". https://doi.org/10.1109/tse.1976.233837.

Harvard

McCabe, T. J. 1976, A Complexity Measure, IEEE Transactions on Software Engineering, available at: https://doi.org/10.1109/tse.1976.233837 [Accessed 8 Aug. 2026].

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Resource details

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Title
A Complexity Measure
Author / contributors
Thomas J. McCabe
Publisher
IEEE Transactions on Software Engineering
Publication year
1976
Language
English

Subjects

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Computer science; Theoretical computer science; Computational complexity theory; Graph; Worst-case complexity; Graph theory; Time complexity; Measure (data warehouse); Descriptive complexity theory; Algorithm; Mathematics; Data mining
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